Papers
8
Total Citations
279
H-Index
6
About
Satoshi Kudoh is a leading researcher in humanoid robotics, whose work has fundamentally advanced how robots achieve dynamic balance, generate natural locomotion, and imitate human motion. His most influential contribution is a feedback balance control system using quadratic programming, which enables humanoid robots to recover from large perturbations in 3D space—a critical capability for real-world operation. He also developed a C² continuous gait-pattern generation method based on an enhanced inverted pendulum model, allowing for smooth, physically feasible bipedal walking. Beyond locomotion, Kudoh pioneered the extraction and imitation of person-specific motion "style," enabling robots to replicate not just the task but the individual nuances of human movement, with applications in entertainment and human-robot interaction. His work on trajectory optimization under physical constraints, using hierarchical B-splines, has been instrumental in transforming recorded human motion into executable robot motions while respecting hardware limits. With over 270 citations across his most-cited papers, Kudoh’s research has shaped the fields of dynamic postural control, gait planning, and motion style transfer. His recent work even extends to robotic manipulation of deformable objects, such as string-tying operations, demonstrating a sustained commitment to solving complex, real-world robotic challenges.
Research Focus
Key Achievements
Top Papers
- 1
- 2The dynamic postural adjustment with the quadratic programming method57 citations · 2003
- 3C/sup 2/ continuous gait-pattern generation for biped robots44 citations · 2004
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